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3D Human Tracking with Catadioptric Omnidirectional Camera

Communication avec acte
Auteur
ABABSA, Fakhreddine
543315 Laboratoire d’Ingénierie des Systèmes Physiques et Numériques [LISPEN]
HADJ-ABDELKADER, Hicham
143247 Informatique, Biologie Intégrative et Systèmes Complexes [IBISC]
BOUI, Marouane
143247 Informatique, Biologie Intégrative et Systèmes Complexes [IBISC]

URI
http://hdl.handle.net/10985/16195
DOI
10.1145/3323873.3325027
Date
2019

Résumé

This paper deals with the problem of 3D human tracking in catadioptric images using particle-filtering framework. While traditional perspective images are well exploited, only a few methods have been developed for catadioptric vision, for the human detection or tracking problems. We propose to extend the 3D pose estimation in the case of perspective cameras to catadioptric sensors. In this paper, we develop an original likelihood functions based, on the one hand, on the geodetic distance in the spherical space SO3 and, on the other hand, on the mapping between the human silhouette in the images and the projected 3D model. These likelihood functions combined with a particle filter, whose propagation model is adapted to the spherical space, allow accurate 3D human tracking in omnidirectional images. Both visual and quantitative analysis of the experimental results demonstrate the effectiveness of our approach.

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LISPEN_ICMR_ABABSA_2019.pdf
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Fin d'embargo:
2019-12-31
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  • Laboratoire d’Ingénierie des Systèmes Physiques Et Numériques (LISPEN)

Documents liés

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  • 3D Human Pose Estimation with a Catadioptric Sensor in Unconstrained Environments Using an Annealed Particle Filter 
    Article dans une revue avec comité de lecture
    ABABSA, Fakhreddine; HADJ-ABDELKADER, Hicham; BOUI, Marouane (MDPI, 2020)
    The purpose of this paper is to investigate the problem of 3D human tracking in complex environments using a particle filter with images captured by a catadioptric vision system. This issue has been widely studied in the ...
  • GMCAD: an original Synthetic Dataset of 2D Designs along their Geometrical and Mechanical Conditions 
    Article dans une revue avec comité de lecture
    ALMASRI, Waad; BETTEBGHOR, Dimitri; ADJED, Faouzi; ABABSA, Fakhreddine; ccDANGLADE, Florence (Elsevier BV, 2022)
    We build an original synthetic dataset of 2D mechanical designs alongside their mechanical and geometric constraints, GMCAD. Such a dataset allows training Deep Learning (DL) models for Design for Additive Manufacturing ...
  • Methodology for the Field Evaluation of the Impact of Augmented Reality Tools for Maintenance Workers in the Aeronautic Industry 
    Article dans une revue avec comité de lecture
    LOIZEAU, Quentin; ABABSA, Fakhreddine; ccMERIENNE, Frédéric; ccDANGLADE, Florence (Frontiers, 2021)
    Augmented Reality (AR) enhances the comprehension of complex situations by making the handling of contextual information easier. Maintenance activities in aeronautics consist of complex tasks carried out on various ...
  • Deep Learning Architecture for Topological Optimized Mechanical Design Generation with Complex Shape Criterion 
    Communication avec acte
    ALMASRI, Waad; BETTEBGHOR, Dimitri; ABABSA, Fakhreddine; ADJED, Faouzi; ccDANGLADE, Florence (Springer International Publishing, 2021)
    Topology optimization is a powerful tool for producing an optimal free-form design from input mechanical constraints. However, in its traditional-density-based approach, it does not feature a proper definition for the ...
  • Combining HoloLens and Leap-Motion for Free Hand-Based 3D Interaction in MR Environments 
    Communication avec acte
    ABABSA, Fakhreddine; HE, Junhui; ccCHARDONNET, Jean-Rémy (Springer International Publishing, 2020)
    The ability to interact with virtual objects using gestures would allow users to improve their experience in Mixed Reality (MR) environments, especially when they use AR headsets. Today, MR head-mounted displays like the ...

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